Bastiaan van Diedenhoven (Columbia University, NASA GISS) - PowerPoint PPT Presentation

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Bastiaan van Diedenhoven (Columbia University, NASA GISS) PowerPoint Presentation
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Bastiaan van Diedenhoven (Columbia University, NASA GISS)

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  1. An investigation of ice crystal sizes and shapes in deep convective clouds using radiance and polarization measurements in conjunction with model simulations Bastiaan van Diedenhoven (Columbia University, NASA GISS) Ann Fridlind, Andrew Ackerman & Brian Cairns (NASA GISS)

  2. Mourning Glory 

  3. CRYSTAL-FACE campaign, Florida 2002 • What are sizes and shapes of ice crystals produced by deep convection? • How do ice crystal vary with location and time? • How are ice crystals affected by aerosols? • MODIS airborne simulator (MAS), • CRS/EPOD Radars, • Research Scanning Polarimeter (RSP), • NAST-I (brightness temperature)

  4. Aircraft flight tracks: 29 July 2002 Adapted from Houze et al. (1980)

  5. Radar ice water content & MAS retrievals OT>4 MAS 11μm Brightness temp Adapted from Houze et al. (1980) MAS Effective radius MAS optical thickness See also Yuan et al., JCLIM, 2010

  6. Particle shapes: Research scanning polarimeter (RSP) • Measures Stokes I, Q & U • Polarized reflectance: • 152 viewing angles ±60° • Wavelengths used: • 865 nm: little absorption • 1880 nm: H2O absorption; sees only very top of cloud RSP measurement

  7. Particle shapes: Research scanning polarimeter (RSP) • Polarized reflectancemainly determined by polarized phase function (P12) of ice crystals • P12 depends strongly on ice shape • particle roughness • Aspect ratio Thin plate Rough plate Thick plate Pristine plate

  8. RSP Polarized reflectance Aspect ratio ~0.1 Thanks to Ping Yang ? Severely roughened ice Aspect ratio ~0.8

  9. 1.88 μm H2O band: very top of cloud 1.88 μm: Very top of cloud 0.87 μm: deeper layers More extreme Aspect ratio deeper in Aspect ratios ~1 at tops of outflow

  10. DHARMA model simulations

  11. DHARMA model simulations(Ackerman et al., Nature 2004; Fridlind et al, science 2004; JGR 2007) • 192 x 192 grid points, ~1km2 resolution, 50-250 m vertical • Liquid, cloud ice and graupel hydrometeor classes • 36 mass-doubling size bins per class • Ice fall speeds modeled assuming mass, area and aspect ratio relationships (Böhm 1989) • Measured ice nuclei (IN) profiles • 29 July: very high IN from African dust, 3 cm-3 (deMott et al., GRL, 2003)

  12. DHARMA model results

  13. DHARMA model results

  14. Sensitivity to IN availability Homogeneous freezing Heterogeneous freezing IN availability

  15. Conclusions 1 • Reff ~18 μm • Rough particles • Aspect ratio ~1 • Reff ~22 μm • Rough particles • Aspect ratio ~0.1 • Rough particles • Aspect ratio ~1.

  16. Conclusions 2 • Polarized reflectance <80o scattering angle not fit well by optical models • Cloud Resolving Model: • Ice crystal sizes sensitive to IN availability • Observed sizes matched only with high IN availability • For more on ice shapes from polarized reflectance come see my poster today: XY74